Upload ModernBERT model
Browse files- 1_Pooling/config.json +10 -0
- README.md +777 -0
- added_tokens.json +6 -0
- config.json +49 -0
- config_sentence_transformers.json +10 -0
- merges.txt +0 -0
- model.safetensors +3 -0
- modules.json +14 -0
- sentence_bert_config.json +4 -0
- special_tokens_map.json +51 -0
- tokenizer.json +0 -0
- tokenizer_config.json +97 -0
- vocab.json +0 -0
1_Pooling/config.json
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@@ -0,0 +1,10 @@
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{
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"word_embedding_dimension": 768,
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"pooling_mode_cls_token": true,
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"pooling_mode_mean_tokens": false,
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"pooling_mode_max_tokens": false,
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"pooling_mode_mean_sqrt_len_tokens": false,
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"pooling_mode_weightedmean_tokens": false,
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"pooling_mode_lasttoken": false,
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"include_prompt": true
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}
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README.md
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@@ -0,0 +1,777 @@
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1 |
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---
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2 |
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tags:
|
3 |
+
- sentence-transformers
|
4 |
+
- sentence-similarity
|
5 |
+
- feature-extraction
|
6 |
+
- generated_from_trainer
|
7 |
+
- dataset_size:901028
|
8 |
+
- loss:CosineSimilarityLoss
|
9 |
+
base_model: Shuu12121/CodeModernBERT-Owl
|
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+
widget:
|
11 |
+
- source_sentence: " public void scan() throws Throwable {\n client = new\
|
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\ FTPClient();\n log.info(\"connecting to \" + host + \"...\");\n \
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\ client.connect(host);\n log.info(client.getReplyString());\n \
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\ log.info(\"logging in...\");\n client.login(\"anonymous\", \"\");\n\
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\ log.info(client.getReplyString());\n Date date = Calendar.getInstance().getTime();\n\
|
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\ xmlDocument = new XMLDocument(host, dir, date);\n scanDirectory(dir);\n\
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\ }\n"
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sentences:
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- " public static void zip(ZipOutputStream out, File f, String base) throws Exception\
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\ {\n if (f.isDirectory()) {\n File[] fl = f.listFiles();\n\
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\ base = base.length() == 0 ? \"\" : base + File.separator;\n \
|
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\ for (int i = 0; i < fl.length; i++) {\n zip(out, fl[i],\
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\ base + fl[i].getName());\n }\n } else {\n out.putNextEntry(new\
|
24 |
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\ org.apache.tools.zip.ZipEntry(base));\n FileInputStream in = new\
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25 |
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\ FileInputStream(f);\n IOUtils.copyStream(in, out);\n in.close();\n\
|
26 |
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\ }\n Thread.sleep(10);\n }\n"
|
27 |
+
- " public static void zip(String destination, String folder) {\n File\
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28 |
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\ fdir = new File(folder);\n File[] files = fdir.listFiles();\n \
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29 |
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\ PrintWriter stdout = new PrintWriter(System.out, true);\n int read =\
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30 |
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\ 0;\n FileInputStream in;\n byte[] data = new byte[1024];\n \
|
31 |
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\ try {\n ZipOutputStream out = new ZipOutputStream(new FileOutputStream(destination));\n\
|
32 |
+
\ out.setMethod(ZipOutputStream.DEFLATED);\n for (int i\
|
33 |
+
\ = 0; i < files.length; i++) {\n try {\n stdout.println(files[i].getName());\n\
|
34 |
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\ ZipEntry entry = new ZipEntry(files[i].getName());\n \
|
35 |
+
\ in = new FileInputStream(files[i].getPath());\n \
|
36 |
+
\ out.putNextEntry(entry);\n while ((read = in.read(data,\
|
37 |
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\ 0, 1024)) != -1) {\n out.write(data, 0, read);\n \
|
38 |
+
\ }\n out.closeEntry();\n \
|
39 |
+
\ in.close();\n } catch (Exception e) {\n e.printStackTrace();\n\
|
40 |
+
\ }\n }\n out.close();\n } catch (IOException\
|
41 |
+
\ ex) {\n ex.printStackTrace();\n }\n }\n"
|
42 |
+
- " private void copyFile(URL from, File to) {\n try {\n InputStream\
|
43 |
+
\ is = from.openStream();\n IOUtils.copy(is, new FileOutputStream(to));\n\
|
44 |
+
\ } catch (IOException e) {\n e.printStackTrace();\n \
|
45 |
+
\ }\n }\n"
|
46 |
+
- source_sentence: " public void createMd5Hash() {\n try {\n \
|
47 |
+
\ String vcardObject = new ContactToVcard(TimeZone.getTimeZone(\"UTC\"), \"UTF-8\"\
|
48 |
+
).convert(this);\n MessageDigest m = MessageDigest.getInstance(\"MD5\"\
|
49 |
+
);\n m.update(vcardObject.getBytes());\n this.md5Hash =\
|
50 |
+
\ new BigInteger(m.digest()).toString();\n if (log.isTraceEnabled())\
|
51 |
+
\ {\n log.trace(\"Hash is:\" + this.md5Hash);\n }\n\
|
52 |
+
\ } catch (ConverterException ex) {\n log.error(\"Error creating\
|
53 |
+
\ hash:\" + ex.getMessage());\n } catch (NoSuchAlgorithmException noSuchAlgorithmException)\
|
54 |
+
\ {\n log.error(\"Error creating hash:\" + noSuchAlgorithmException.getMessage());\n\
|
55 |
+
\ }\n }\n"
|
56 |
+
sentences:
|
57 |
+
- " public static void main(String[] args) {\n try {\n int\
|
58 |
+
\ encodeFlag = 0;\n if (args[0].equals(\"-e\")) {\n \
|
59 |
+
\ encodeFlag = Base64.ENCODE;\n } else if (args[0].equals(\"-d\"))\
|
60 |
+
\ {\n encodeFlag = Base64.DECODE;\n }\n String\
|
61 |
+
\ infile = args[1];\n String outfile = args[2];\n File fin\
|
62 |
+
\ = new File(infile);\n FileInputStream fis = new FileInputStream(fin);\n\
|
63 |
+
\ BufferedInputStream bis = new BufferedInputStream(fis);\n \
|
64 |
+
\ Base64.InputStream b64in = new Base64.InputStream(bis, encodeFlag | Base64.DO_BREAK_LINES);\n\
|
65 |
+
\ File fout = new File(outfile);\n FileOutputStream fos\
|
66 |
+
\ = new FileOutputStream(fout);\n BufferedOutputStream bos = new BufferedOutputStream(fos);\n\
|
67 |
+
\ byte[] buff = new byte[1024];\n int read = -1;\n \
|
68 |
+
\ while ((read = b64in.read(buff)) >= 0) {\n bos.write(buff,\
|
69 |
+
\ 0, read);\n }\n bos.close();\n b64in.close();\n\
|
70 |
+
\ } catch (Exception e) {\n e.printStackTrace();\n }\n\
|
71 |
+
\ }\n"
|
72 |
+
- " public static String md5(String str) {\n StringBuffer buf = new StringBuffer();\n\
|
73 |
+
\ try {\n MessageDigest md = MessageDigest.getInstance(\"MD5\"\
|
74 |
+
);\n byte[] data = new byte[32];\n md.update(str.getBytes(md5Encoding),\
|
75 |
+
\ 0, str.length());\n data = md.digest();\n for (int i =\
|
76 |
+
\ 0; i < data.length; i++) {\n int halfbyte = (data[i] >>> 4) &\
|
77 |
+
\ 0x0F;\n int two_halfs = 0;\n do {\n \
|
78 |
+
\ if ((0 <= halfbyte) && (halfbyte <= 9)) buf.append((char) ('0' + halfbyte));\
|
79 |
+
\ else buf.append((char) ('a' + (halfbyte - 10)));\n halfbyte\
|
80 |
+
\ = data[i] & 0x0F;\n } while (two_halfs++ < 1);\n }\n\
|
81 |
+
\ } catch (Exception e) {\n errorLog(\"{Malgn.md5} \" + e.getMessage());\n\
|
82 |
+
\ }\n return buf.toString();\n }\n"
|
83 |
+
- " public static String md5(String text, String charset) {\n MessageDigest\
|
84 |
+
\ msgDigest = null;\n try {\n msgDigest = MessageDigest.getInstance(\"\
|
85 |
+
MD5\");\n } catch (NoSuchAlgorithmException e) {\n throw new\
|
86 |
+
\ IllegalStateException(\"System doesn't support MD5 algorithm.\");\n }\n\
|
87 |
+
\ msgDigest.update(text.getBytes());\n byte[] bytes = msgDigest.digest();\n\
|
88 |
+
\ byte tb;\n char low;\n char high;\n char tmpChar;\n\
|
89 |
+
\ String md5Str = new String();\n for (int i = 0; i < bytes.length;\
|
90 |
+
\ i++) {\n tb = bytes[i];\n tmpChar = (char) ((tb >>> 4)\
|
91 |
+
\ & 0x000f);\n if (tmpChar >= 10) {\n high = (char)\
|
92 |
+
\ (('a' + tmpChar) - 10);\n } else {\n high = (char)\
|
93 |
+
\ ('0' + tmpChar);\n }\n md5Str += high;\n tmpChar\
|
94 |
+
\ = (char) (tb & 0x000f);\n if (tmpChar >= 10) {\n low\
|
95 |
+
\ = (char) (('a' + tmpChar) - 10);\n } else {\n low\
|
96 |
+
\ = (char) ('0' + tmpChar);\n }\n md5Str += low;\n \
|
97 |
+
\ }\n return md5Str;\n }\n"
|
98 |
+
- source_sentence: " @Override\n public void run() {\n \
|
99 |
+
\ try {\n IOUtils.copy(getSource(), processStdIn);\n\
|
100 |
+
\ System.err.println(\"Copy done.\");\n \
|
101 |
+
\ close();\n } catch (IOException e) {\n e.printStackTrace();\n\
|
102 |
+
\ IOUtils.closeQuietly(ExternalDecoder.this);\n \
|
103 |
+
\ }\n }\n"
|
104 |
+
sentences:
|
105 |
+
- " private String readJsonString() {\n StringBuilder builder = new StringBuilder();\n\
|
106 |
+
\ HttpClient client = new DefaultHttpClient();\n HttpGet httpGet\
|
107 |
+
\ = new HttpGet(SERVER_URL);\n try {\n HttpResponse response\
|
108 |
+
\ = client.execute(httpGet);\n StatusLine statusLine = response.getStatusLine();\n\
|
109 |
+
\ int statusCode = statusLine.getStatusCode();\n if (statusCode\
|
110 |
+
\ == 200) {\n HttpEntity entity = response.getEntity();\n \
|
111 |
+
\ InputStream content = entity.getContent();\n BufferedReader\
|
112 |
+
\ reader = new BufferedReader(new InputStreamReader(content));\n \
|
113 |
+
\ String line;\n while ((line = reader.readLine()) != null) {\n\
|
114 |
+
\ builder.append(line);\n }\n } else\
|
115 |
+
\ {\n Log.e(TAG, \"Failed to download file\");\n }\n\
|
116 |
+
\ } catch (ClientProtocolException e) {\n e.printStackTrace();\n\
|
117 |
+
\ } catch (IOException e) {\n e.printStackTrace();\n \
|
118 |
+
\ }\n return builder.toString();\n }\n"
|
119 |
+
- " public void run() {\n LogPrinter.log(Level.FINEST, \"Started Download\
|
120 |
+
\ at : {0, date, long}\", new Date());\n if (!PipeConnected) {\n \
|
121 |
+
\ throw new IllegalStateException(\"You should connect the pipe before with\
|
122 |
+
\ getInputStream()\");\n }\n InputStream ins = null;\n if\
|
123 |
+
\ (IsAlreadyDownloaded) {\n LogPrinter.log(Level.FINEST, \"The file\
|
124 |
+
\ already Exists open and foward the byte\");\n try {\n \
|
125 |
+
\ ContentLength = (int) TheAskedFile.length();\n ContentType\
|
126 |
+
\ = URLConnection.getFileNameMap().getContentTypeFor(TheAskedFile.getName());\n\
|
127 |
+
\ ins = new FileInputStream(TheAskedFile);\n byte[]\
|
128 |
+
\ buffer = new byte[BUFFER_SIZE];\n int read = ins.read(buffer);\n\
|
129 |
+
\ while (read >= 0) {\n Pipe.write(buffer, 0,\
|
130 |
+
\ read);\n read = ins.read(buffer);\n }\n \
|
131 |
+
\ } catch (IOException e) {\n e.printStackTrace();\n \
|
132 |
+
\ } finally {\n if (ins != null) {\n \
|
133 |
+
\ try {\n ins.close();\n } catch\
|
134 |
+
\ (IOException e) {\n }\n }\n }\n\
|
135 |
+
\ } else {\n LogPrinter.log(Level.FINEST, \"the file does not\
|
136 |
+
\ exist locally so we try to download the thing\");\n File theDir =\
|
137 |
+
\ TheAskedFile.getParentFile();\n if (!theDir.exists()) {\n \
|
138 |
+
\ theDir.mkdirs();\n }\n for (URL url : ListFastest)\
|
139 |
+
\ {\n FileOutputStream fout = null;\n boolean OnError\
|
140 |
+
\ = false;\n long timestart = System.currentTimeMillis();\n \
|
141 |
+
\ long bytecount = 0;\n try {\n \
|
142 |
+
\ URL newUrl = new URL(url.toString() + RequestedFile);\n LogPrinter.log(Level.FINEST,\
|
143 |
+
\ \"the download URL = {0}\", newUrl);\n URLConnection conn\
|
144 |
+
\ = newUrl.openConnection();\n ContentType = conn.getContentType();\n\
|
145 |
+
\ ContentLength = conn.getContentLength();\n \
|
146 |
+
\ ins = conn.getInputStream();\n fout = new FileOutputStream(TheAskedFile);\n\
|
147 |
+
\ byte[] buffer = new byte[BUFFER_SIZE];\n \
|
148 |
+
\ int read = ins.read(buffer);\n while (read >= 0) {\n \
|
149 |
+
\ fout.write(buffer, 0, read);\n \
|
150 |
+
\ Pipe.write(buffer, 0, read);\n read = ins.read(buffer);\n\
|
151 |
+
\ bytecount += read;\n }\n \
|
152 |
+
\ Pipe.flush();\n } catch (IOException e) {\n \
|
153 |
+
\ OnError = true;\n } finally {\n \
|
154 |
+
\ if (ins != null) {\n try {\n \
|
155 |
+
\ ins.close();\n } catch (IOException e) {\n \
|
156 |
+
\ }\n }\n if (fout !=\
|
157 |
+
\ null) {\n try {\n fout.close();\n\
|
158 |
+
\ } catch (IOException e) {\n }\n\
|
159 |
+
\ }\n }\n long timeend = System.currentTimeMillis();\n\
|
160 |
+
\ if (OnError) {\n continue;\n \
|
161 |
+
\ } else {\n long timetook = timeend - timestart;\n \
|
162 |
+
\ BigDecimal speed = new BigDecimal(bytecount).multiply(new BigDecimal(1000)).divide(new\
|
163 |
+
\ BigDecimal(timetook), MathContext.DECIMAL32);\n for (ReportCalculatedStatistique\
|
164 |
+
\ report : Listener) {\n report.reportUrlStat(url, speed,\
|
165 |
+
\ timetook);\n }\n break;\n \
|
166 |
+
\ }\n }\n }\n LogPrinter.log(Level.FINEST, \"download\
|
167 |
+
\ finished at {0,date,long}\", new Date());\n if (Pipe != null) {\n \
|
168 |
+
\ try {\n Pipe.close();\n } catch (IOException\
|
169 |
+
\ e) {\n e.printStackTrace();\n }\n }\n }\n"
|
170 |
+
- " public void run(String srcf, String dst) {\n final Path srcPath =\
|
171 |
+
\ new Path(\"./\" + srcf);\n final Path desPath = new Path(dst);\n \
|
172 |
+
\ try {\n Path[] srcs = FileUtil.stat2Paths(hdfs.globStatus(srcPath),\
|
173 |
+
\ srcPath);\n OutputStream out = FileSystem.getLocal(conf).create(desPath);\n\
|
174 |
+
\ for (int i = 0; i < srcs.length; i++) {\n System.out.println(srcs[i]);\n\
|
175 |
+
\ InputStream in = hdfs.open(srcs[i]);\n IOUtils.copyBytes(in,\
|
176 |
+
\ out, conf, false);\n in.close();\n }\n \
|
177 |
+
\ out.close();\n } catch (IOException ex) {\n System.err.print(ex.getMessage());\n\
|
178 |
+
\ }\n }\n"
|
179 |
+
- source_sentence: " private void readHomePage(ITestThread testThread) throws IOException\
|
180 |
+
\ {\n if (null == testThread) {\n throw new IllegalArgumentException(\"\
|
181 |
+
Test thread may not be null.\");\n }\n final InputStream urlIn =\
|
182 |
+
\ new URL(testUrl).openStream();\n final int availableBytes = urlIn.available();\n\
|
183 |
+
\ if (0 == availableBytes) {\n throw new IllegalStateException(\"\
|
184 |
+
Zero bytes on target host.\");\n }\n in = new BufferedReader(new\
|
185 |
+
\ InputStreamReader(urlIn));\n String line;\n while (null != in\
|
186 |
+
\ && null != (line = in.readLine())) {\n page.append(line);\n \
|
187 |
+
\ page.append('\\n');\n if (0 != lineDelay) {\n \
|
188 |
+
\ OS.sleep(lineDelay);\n }\n if (testThread.isActionStopped())\
|
189 |
+
\ {\n break;\n }\n }\n }\n"
|
190 |
+
sentences:
|
191 |
+
- " @Override\n public ReturnValue do_run() {\n int bufLen = 500 *\
|
192 |
+
\ 1024;\n ReturnValue ret = new ReturnValue();\n ret.setExitStatus(ReturnValue.SUCCESS);\n\
|
193 |
+
\ File output = null;\n if (((String) options.valueOf(\"input-file\"\
|
194 |
+
)).startsWith(\"s3://\")) {\n Pattern p = Pattern.compile(\"s3://(\\\
|
195 |
+
\\S+):(\\\\S+)@(\\\\S+)\");\n Matcher m = p.matcher((String) options.valueOf(\"\
|
196 |
+
input-file\"));\n boolean result = m.find();\n String accessKey\
|
197 |
+
\ = null;\n String secretKey = null;\n String URL = (String)\
|
198 |
+
\ options.valueOf(\"input-file\");\n if (result) {\n \
|
199 |
+
\ accessKey = m.group(1);\n secretKey = m.group(2);\n \
|
200 |
+
\ URL = \"s3://\" + m.group(3);\n } else {\n \
|
201 |
+
\ try {\n HashMap<String, String> settings = (HashMap<String,\
|
202 |
+
\ String>) ConfigTools.getSettings();\n accessKey = settings.get(\"\
|
203 |
+
AWS_ACCESS_KEY\");\n secretKey = settings.get(\"AWS_SECRET_KEY\"\
|
204 |
+
);\n } catch (Exception e) {\n ret.setExitStatus(ReturnValue.SETTINGSFILENOTFOUND);\n\
|
205 |
+
\ ret.setProcessExitStatus(ReturnValue.SETTINGSFILENOTFOUND);\n\
|
206 |
+
\ return (ret);\n }\n }\n \
|
207 |
+
\ if (accessKey == null || secretKey == null) {\n ret.setExitStatus(ReturnValue.ENVVARNOTFOUND);\n\
|
208 |
+
\ ret.setProcessExitStatus(ReturnValue.ENVVARNOTFOUND);\n \
|
209 |
+
\ return (ret);\n }\n AmazonS3 s3 = new AmazonS3Client(new\
|
210 |
+
\ BasicAWSCredentials(accessKey, secretKey));\n p = Pattern.compile(\"\
|
211 |
+
s3://([^/]+)/(\\\\S+)\");\n m = p.matcher(URL);\n result\
|
212 |
+
\ = m.find();\n if (result) {\n String bucket = m.group(1);\n\
|
213 |
+
\ String key = m.group(2);\n S3Object object = s3.getObject(new\
|
214 |
+
\ GetObjectRequest(bucket, key));\n System.out.println(\"Content-Type:\
|
215 |
+
\ \" + object.getObjectMetadata().getContentType());\n output =\
|
216 |
+
\ new File((String) options.valueOf(\"output-dir\") + File.separator + key);\n\
|
217 |
+
\ output.getParentFile().mkdirs();\n if (!output.exists()\
|
218 |
+
\ || output.length() != object.getObjectMetadata().getContentLength()) {\n \
|
219 |
+
\ System.out.println(\"Downloading an S3 object from bucket: \"\
|
220 |
+
\ + bucket + \" with key: \" + key);\n BufferedInputStream\
|
221 |
+
\ reader = new BufferedInputStream(object.getObjectContent(), bufLen);\n \
|
222 |
+
\ try {\n BufferedOutputStream writer = new\
|
223 |
+
\ BufferedOutputStream(new FileOutputStream(output), bufLen);\n \
|
224 |
+
\ while (true) {\n int data = reader.read();\n\
|
225 |
+
\ if (data == -1) {\n \
|
226 |
+
\ break;\n }\n writer.write(data);\n\
|
227 |
+
\ }\n reader.close();\n \
|
228 |
+
\ writer.close();\n } catch (FileNotFoundException\
|
229 |
+
\ e) {\n System.err.println(e.getMessage());\n \
|
230 |
+
\ } catch (IOException e) {\n System.err.println(e.getMessage());\n\
|
231 |
+
\ }\n } else {\n System.out.println(\"\
|
232 |
+
Skipping download of S3 object from bucket: \" + bucket + \" with key: \" + key\
|
233 |
+
\ + \" since local output exists: \" + output.getAbsolutePath());\n \
|
234 |
+
\ }\n }\n } else if (((String) options.valueOf(\"input-file\"\
|
235 |
+
)).startsWith(\"http://\") || ((String) options.valueOf(\"input-file\")).startsWith(\"\
|
236 |
+
https://\")) {\n Pattern p = Pattern.compile(\"(https*)://(\\\\S+):(\\\
|
237 |
+
\\S+)@(\\\\S+)\");\n Matcher m = p.matcher((String) options.valueOf(\"\
|
238 |
+
input-file\"));\n boolean result = m.find();\n String protocol\
|
239 |
+
\ = null;\n String user = null;\n String pass = null;\n\
|
240 |
+
\ String URL = (String) options.valueOf(\"input-file\");\n \
|
241 |
+
\ if (result) {\n protocol = m.group(1);\n user\
|
242 |
+
\ = m.group(2);\n pass = m.group(3);\n URL = protocol\
|
243 |
+
\ + \"://\" + m.group(4);\n }\n URL urlObj = null;\n \
|
244 |
+
\ try {\n urlObj = new URL(URL);\n if (urlObj\
|
245 |
+
\ != null) {\n URLConnection urlConn = urlObj.openConnection();\n\
|
246 |
+
\ if (user != null && pass != null) {\n \
|
247 |
+
\ String userPassword = user + \":\" + pass;\n String\
|
248 |
+
\ encoding = new Base64().encodeBase64String(userPassword.getBytes());\n \
|
249 |
+
\ urlConn.setRequestProperty(\"Authorization\", \"Basic \" +\
|
250 |
+
\ encoding);\n }\n p = Pattern.compile(\"\
|
251 |
+
://([^/]+)/(\\\\S+)\");\n m = p.matcher(URL);\n \
|
252 |
+
\ result = m.find();\n if (result) {\n \
|
253 |
+
\ String host = m.group(1);\n String path =\
|
254 |
+
\ m.group(2);\n output = new File((String) options.valueOf(\"\
|
255 |
+
output-dir\") + path);\n output.getParentFile().mkdirs();\n\
|
256 |
+
\ if (!output.exists() || output.length() != urlConn.getContentLength())\
|
257 |
+
\ {\n System.out.println(\"Downloading an http object\
|
258 |
+
\ from URL: \" + URL);\n BufferedInputStream reader\
|
259 |
+
\ = new BufferedInputStream(urlConn.getInputStream(), bufLen);\n \
|
260 |
+
\ BufferedOutputStream writer = new BufferedOutputStream(new FileOutputStream(output),\
|
261 |
+
\ bufLen);\n while (true) {\n \
|
262 |
+
\ int data = reader.read();\n if (data\
|
263 |
+
\ == -1) {\n break;\n \
|
264 |
+
\ }\n writer.write(data);\n \
|
265 |
+
\ }\n reader.close();\n \
|
266 |
+
\ writer.close();\n } else {\n \
|
267 |
+
\ System.out.println(\"Skipping download of http object from\
|
268 |
+
\ URL: \" + URL + \" since local output exists: \" + output.getAbsolutePath());\n\
|
269 |
+
\ }\n }\n }\n \
|
270 |
+
\ } catch (MalformedURLException e) {\n System.err.println(e.getMessage());\n\
|
271 |
+
\ } catch (IOException e) {\n System.err.println(e.getMessage());\n\
|
272 |
+
\ }\n } else {\n output = new File((String) options.valueOf(\"\
|
273 |
+
input-file\"));\n }\n boolean result = FileTools.unzipFile(output,\
|
274 |
+
\ new File((String) options.valueOf(\"output-dir\")));\n if (!result) {\n\
|
275 |
+
\ ret.setStderr(\"Can't unzip software bundle \" + options.valueOf(\"\
|
276 |
+
input-file\") + \" to directory \" + options.valueOf(\"output-dir\"));\n \
|
277 |
+
\ ret.setExitStatus(ReturnValue.RUNTIMEEXCEPTION);\n }\n return\
|
278 |
+
\ (ret);\n }\n"
|
279 |
+
- " public void writeConfigurationFile() throws IOException, ComponentException\
|
280 |
+
\ {\n SystemConfig config = parent.getParentSystem().getConfiguration();\n\
|
281 |
+
\ File original = config.getLocation();\n File backup = new File(original.getParentFile(),\
|
282 |
+
\ original.getName() + \".\" + System.currentTimeMillis());\n FileInputStream\
|
283 |
+
\ in = new FileInputStream(original);\n FileOutputStream out = new FileOutputStream(backup);\n\
|
284 |
+
\ byte[] buffer = new byte[2048];\n try {\n int bytesread\
|
285 |
+
\ = 0;\n while ((bytesread = in.read(buffer)) > 0) {\n \
|
286 |
+
\ out.write(buffer, 0, bytesread);\n }\n } catch (IOException\
|
287 |
+
\ e) {\n logger.warn(\"Failed to copy backup of configuration file\"\
|
288 |
+
);\n throw e;\n } finally {\n in.close();\n \
|
289 |
+
\ out.close();\n }\n FileWriter replace = new FileWriter(original);\n\
|
290 |
+
\ replace.write(config.toFileFormat());\n replace.close();\n \
|
291 |
+
\ logger.info(\"Re-wrote configuration file \" + original.getPath());\n \
|
292 |
+
\ }\n"
|
293 |
+
- " @Override\n protected void doGet(HttpServletRequest req, HttpServletResponse\
|
294 |
+
\ resp) throws ServletException, IOException {\n resp.addHeader(\"Cache-Control\"\
|
295 |
+
, \"max-age=\" + Constants.HTTP_CACHE_SECONDS);\n String uuid = req.getRequestURI().substring(req.getRequestURI().indexOf(Constants.SERVLET_FULL_PREFIX)\
|
296 |
+
\ + Constants.SERVLET_FULL_PREFIX.length() + 1);\n boolean notScale = ClientUtils.toBoolean(req.getParameter(Constants.URL_PARAM_NOT_SCALE));\n\
|
297 |
+
\ ServletOutputStream os = resp.getOutputStream();\n if (uuid !=\
|
298 |
+
\ null && !\"\".equals(uuid)) {\n try {\n String mimetype\
|
299 |
+
\ = fedoraAccess.getMimeTypeForStream(uuid, FedoraUtils.IMG_FULL_STREAM);\n \
|
300 |
+
\ if (mimetype == null) {\n mimetype = \"image/jpeg\"\
|
301 |
+
;\n }\n ImageMimeType loadFromMimeType = ImageMimeType.loadFromMimeType(mimetype);\n\
|
302 |
+
\ if (loadFromMimeType == ImageMimeType.JPEG || loadFromMimeType\
|
303 |
+
\ == ImageMimeType.PNG) {\n StringBuffer sb = new StringBuffer();\n\
|
304 |
+
\ sb.append(config.getFedoraHost()).append(\"/objects/\").append(uuid).append(\"\
|
305 |
+
/datastreams/IMG_FULL/content\");\n InputStream is = RESTHelper.get(sb.toString(),\
|
306 |
+
\ config.getFedoraLogin(), config.getFedoraPassword(), false);\n \
|
307 |
+
\ if (is == null) {\n return;\n \
|
308 |
+
\ }\n try {\n IOUtils.copyStreams(is,\
|
309 |
+
\ os);\n } catch (IOException e) {\n \
|
310 |
+
\ resp.setStatus(HttpURLConnection.HTTP_NOT_FOUND);\n \
|
311 |
+
\ LOGGER.error(\"Unable to open full image.\", e);\n } finally\
|
312 |
+
\ {\n os.flush();\n if (is != null)\
|
313 |
+
\ {\n try {\n is.close();\n\
|
314 |
+
\ } catch (IOException e) {\n \
|
315 |
+
\ resp.setStatus(HttpURLConnection.HTTP_NOT_FOUND);\n \
|
316 |
+
\ LOGGER.error(\"Unable to close stream.\", e);\n \
|
317 |
+
\ } finally {\n is = null;\n \
|
318 |
+
\ }\n }\n }\n\
|
319 |
+
\ } else {\n Image rawImg = KrameriusImageSupport.readImage(uuid,\
|
320 |
+
\ FedoraUtils.IMG_FULL_STREAM, this.fedoraAccess, 0, loadFromMimeType);\n \
|
321 |
+
\ BufferedImage scaled = null;\n if (!notScale)\
|
322 |
+
\ {\n scaled = KrameriusImageSupport.getSmallerImage(rawImg,\
|
323 |
+
\ 1250, 1000);\n } else {\n scaled =\
|
324 |
+
\ KrameriusImageSupport.getSmallerImage(rawImg, 2500, 2000);\n \
|
325 |
+
\ }\n KrameriusImageSupport.writeImageToStream(scaled,\
|
326 |
+
\ \"JPG\", os);\n resp.setContentType(ImageMimeType.JPEG.getValue());\n\
|
327 |
+
\ resp.setStatus(HttpURLConnection.HTTP_OK);\n \
|
328 |
+
\ }\n } catch (IOException e) {\n resp.setStatus(HttpURLConnection.HTTP_NOT_FOUND);\n\
|
329 |
+
\ LOGGER.error(\"Unable to open full image.\", e);\n \
|
330 |
+
\ } catch (XPathExpressionException e) {\n resp.setStatus(HttpURLConnection.HTTP_NOT_FOUND);\n\
|
331 |
+
\ LOGGER.error(\"Unable to create XPath expression.\", e);\n \
|
332 |
+
\ } finally {\n os.flush();\n }\n }\n\
|
333 |
+
\ }\n"
|
334 |
+
- source_sentence: " public static boolean insert(final Cargo cargo) {\n \
|
335 |
+
\ int result = 0;\n final Connection c = DBConnection.getConnection();\n\
|
336 |
+
\ PreparedStatement pst = null;\n if (c == null) {\n \
|
337 |
+
\ return false;\n }\n try {\n c.setAutoCommit(false);\n\
|
338 |
+
\ final String sql = \"insert into cargo (nome) values (?)\";\n \
|
339 |
+
\ pst = c.prepareStatement(sql);\n pst.setString(1, cargo.getNome());\n\
|
340 |
+
\ result = pst.executeUpdate();\n c.commit();\n }\
|
341 |
+
\ catch (final SQLException e) {\n try {\n c.rollback();\n\
|
342 |
+
\ } catch (final SQLException e1) {\n e1.printStackTrace();\n\
|
343 |
+
\ }\n System.out.println(\"[CargoDAO.insert] Erro ao inserir\
|
344 |
+
\ -> \" + e.getMessage());\n } finally {\n DBConnection.closePreparedStatement(pst);\n\
|
345 |
+
\ DBConnection.closeConnection(c);\n }\n if (result >\
|
346 |
+
\ 0) {\n return true;\n } else {\n return false;\n\
|
347 |
+
\ }\n }\n"
|
348 |
+
sentences:
|
349 |
+
- " public String md5sum(String toCompute) throws Exception {\n MessageDigest\
|
350 |
+
\ md = MessageDigest.getInstance(\"MD5\");\n md.update(toCompute.getBytes());\n\
|
351 |
+
\ java.math.BigInteger hash = new java.math.BigInteger(1, md.digest());\n\
|
352 |
+
\ return hash.toString(16);\n }\n"
|
353 |
+
- " protected void runTest(URL pBaseURL, String pName, String pHref) throws Exception\
|
354 |
+
\ {\n URL url = new URL(pBaseURL, pHref);\n XSParser parser = new\
|
355 |
+
\ XSParser();\n parser.setValidating(false);\n InputSource isource\
|
356 |
+
\ = new InputSource(url.openStream());\n isource.setSystemId(url.toString());\n\
|
357 |
+
\ String result;\n try {\n parser.parse(isource);\n \
|
358 |
+
\ ++numOk;\n result = \"Ok\";\n } catch (Exception\
|
359 |
+
\ e) {\n ++numFailed;\n result = e.getMessage();\n \
|
360 |
+
\ }\n log(\"Running test \" + pName + \" with URL \" + url + \": \" +\
|
361 |
+
\ result);\n }\n"
|
362 |
+
- " public String generateMappackMD5(File mapPackFile) throws IOException, NoSuchAlgorithmException\
|
363 |
+
\ {\n ZipFile zip = new ZipFile(mapPackFile);\n try {\n \
|
364 |
+
\ Enumeration<? extends ZipEntry> entries = zip.entries();\n MessageDigest\
|
365 |
+
\ md5Total = MessageDigest.getInstance(\"MD5\");\n MessageDigest md5\
|
366 |
+
\ = MessageDigest.getInstance(\"MD5\");\n while (entries.hasMoreElements())\
|
367 |
+
\ {\n ZipEntry entry = entries.nextElement();\n \
|
368 |
+
\ if (entry.isDirectory()) continue;\n String name = entry.getName();\n\
|
369 |
+
\ if (name.toUpperCase().startsWith(\"META-INF\")) continue;\n\
|
370 |
+
\ md5.reset();\n InputStream in = zip.getInputStream(entry);\n\
|
371 |
+
\ byte[] data = Utilities.getInputBytes(in);\n in.close();\n\
|
372 |
+
\ byte[] digest = md5.digest(data);\n log.trace(\"\
|
373 |
+
Hashsum \" + Hex.encodeHexString(digest) + \" includes \\\"\" + name + \"\\\"\"\
|
374 |
+
);\n md5Total.update(digest);\n md5Total.update(name.getBytes());\n\
|
375 |
+
\ }\n String md5sum = Hex.encodeHexString(md5Total.digest());\n\
|
376 |
+
\ log.trace(\"md5sum of \" + mapPackFile.getName() + \": \" + md5sum);\n\
|
377 |
+
\ return md5sum;\n } finally {\n zip.close();\n \
|
378 |
+
\ }\n }\n"
|
379 |
+
pipeline_tag: sentence-similarity
|
380 |
+
library_name: sentence-transformers
|
381 |
+
metrics:
|
382 |
+
- pearson_cosine
|
383 |
+
- spearman_cosine
|
384 |
+
model-index:
|
385 |
+
- name: SentenceTransformer based on Shuu12121/CodeModernBERT-Owl
|
386 |
+
results:
|
387 |
+
- task:
|
388 |
+
type: semantic-similarity
|
389 |
+
name: Semantic Similarity
|
390 |
+
dataset:
|
391 |
+
name: val
|
392 |
+
type: val
|
393 |
+
metrics:
|
394 |
+
- type: pearson_cosine
|
395 |
+
value: 0.9481467499740959
|
396 |
+
name: Pearson Cosine
|
397 |
+
- type: spearman_cosine
|
398 |
+
value: 0.5635084463158045
|
399 |
+
name: Spearman Cosine
|
400 |
+
---
|
401 |
+
|
402 |
+
# SentenceTransformer based on Shuu12121/CodeModernBERT-Owl
|
403 |
+
|
404 |
+
This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [Shuu12121/CodeModernBERT-Owl](https://huggingface.co/Shuu12121/CodeModernBERT-Owl). It maps sentences & paragraphs to a 768-dimensional dense vector space and can be used for semantic textual similarity, semantic search, paraphrase mining, text classification, clustering, and more.
|
405 |
+
|
406 |
+
## Model Details
|
407 |
+
|
408 |
+
### Model Description
|
409 |
+
- **Model Type:** Sentence Transformer
|
410 |
+
- **Base model:** [Shuu12121/CodeModernBERT-Owl](https://huggingface.co/Shuu12121/CodeModernBERT-Owl) <!-- at revision c6b9f919885bc8b27718df3af11dc0fbed7e2b63 -->
|
411 |
+
- **Maximum Sequence Length:** 2048 tokens
|
412 |
+
- **Output Dimensionality:** 768 dimensions
|
413 |
+
- **Similarity Function:** Cosine Similarity
|
414 |
+
<!-- - **Training Dataset:** Unknown -->
|
415 |
+
<!-- - **Language:** Unknown -->
|
416 |
+
<!-- - **License:** Unknown -->
|
417 |
+
|
418 |
+
### Model Sources
|
419 |
+
|
420 |
+
- **Documentation:** [Sentence Transformers Documentation](https://sbert.net)
|
421 |
+
- **Repository:** [Sentence Transformers on GitHub](https://github.com/UKPLab/sentence-transformers)
|
422 |
+
- **Hugging Face:** [Sentence Transformers on Hugging Face](https://huggingface.co/models?library=sentence-transformers)
|
423 |
+
|
424 |
+
### Full Model Architecture
|
425 |
+
|
426 |
+
```
|
427 |
+
SentenceTransformer(
|
428 |
+
(0): Transformer({'max_seq_length': 2048, 'do_lower_case': False}) with Transformer model: ModernBertModel
|
429 |
+
(1): Pooling({'word_embedding_dimension': 768, 'pooling_mode_cls_token': True, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True})
|
430 |
+
)
|
431 |
+
```
|
432 |
+
|
433 |
+
## Usage
|
434 |
+
|
435 |
+
### Direct Usage (Sentence Transformers)
|
436 |
+
|
437 |
+
First install the Sentence Transformers library:
|
438 |
+
|
439 |
+
```bash
|
440 |
+
pip install -U sentence-transformers
|
441 |
+
```
|
442 |
+
|
443 |
+
Then you can load this model and run inference.
|
444 |
+
```python
|
445 |
+
from sentence_transformers import SentenceTransformer
|
446 |
+
|
447 |
+
# Download from the 🤗 Hub
|
448 |
+
model = SentenceTransformer("sentence_transformers_model_id")
|
449 |
+
# Run inference
|
450 |
+
sentences = [
|
451 |
+
' public static boolean insert(final Cargo cargo) {\n int result = 0;\n final Connection c = DBConnection.getConnection();\n PreparedStatement pst = null;\n if (c == null) {\n return false;\n }\n try {\n c.setAutoCommit(false);\n final String sql = "insert into cargo (nome) values (?)";\n pst = c.prepareStatement(sql);\n pst.setString(1, cargo.getNome());\n result = pst.executeUpdate();\n c.commit();\n } catch (final SQLException e) {\n try {\n c.rollback();\n } catch (final SQLException e1) {\n e1.printStackTrace();\n }\n System.out.println("[CargoDAO.insert] Erro ao inserir -> " + e.getMessage());\n } finally {\n DBConnection.closePreparedStatement(pst);\n DBConnection.closeConnection(c);\n }\n if (result > 0) {\n return true;\n } else {\n return false;\n }\n }\n',
|
452 |
+
' protected void runTest(URL pBaseURL, String pName, String pHref) throws Exception {\n URL url = new URL(pBaseURL, pHref);\n XSParser parser = new XSParser();\n parser.setValidating(false);\n InputSource isource = new InputSource(url.openStream());\n isource.setSystemId(url.toString());\n String result;\n try {\n parser.parse(isource);\n ++numOk;\n result = "Ok";\n } catch (Exception e) {\n ++numFailed;\n result = e.getMessage();\n }\n log("Running test " + pName + " with URL " + url + ": " + result);\n }\n',
|
453 |
+
' public String generateMappackMD5(File mapPackFile) throws IOException, NoSuchAlgorithmException {\n ZipFile zip = new ZipFile(mapPackFile);\n try {\n Enumeration<? extends ZipEntry> entries = zip.entries();\n MessageDigest md5Total = MessageDigest.getInstance("MD5");\n MessageDigest md5 = MessageDigest.getInstance("MD5");\n while (entries.hasMoreElements()) {\n ZipEntry entry = entries.nextElement();\n if (entry.isDirectory()) continue;\n String name = entry.getName();\n if (name.toUpperCase().startsWith("META-INF")) continue;\n md5.reset();\n InputStream in = zip.getInputStream(entry);\n byte[] data = Utilities.getInputBytes(in);\n in.close();\n byte[] digest = md5.digest(data);\n log.trace("Hashsum " + Hex.encodeHexString(digest) + " includes \\"" + name + "\\"");\n md5Total.update(digest);\n md5Total.update(name.getBytes());\n }\n String md5sum = Hex.encodeHexString(md5Total.digest());\n log.trace("md5sum of " + mapPackFile.getName() + ": " + md5sum);\n return md5sum;\n } finally {\n zip.close();\n }\n }\n',
|
454 |
+
]
|
455 |
+
embeddings = model.encode(sentences)
|
456 |
+
print(embeddings.shape)
|
457 |
+
# [3, 768]
|
458 |
+
|
459 |
+
# Get the similarity scores for the embeddings
|
460 |
+
similarities = model.similarity(embeddings, embeddings)
|
461 |
+
print(similarities.shape)
|
462 |
+
# [3, 3]
|
463 |
+
```
|
464 |
+
|
465 |
+
<!--
|
466 |
+
### Direct Usage (Transformers)
|
467 |
+
|
468 |
+
<details><summary>Click to see the direct usage in Transformers</summary>
|
469 |
+
|
470 |
+
</details>
|
471 |
+
-->
|
472 |
+
|
473 |
+
<!--
|
474 |
+
### Downstream Usage (Sentence Transformers)
|
475 |
+
|
476 |
+
You can finetune this model on your own dataset.
|
477 |
+
|
478 |
+
<details><summary>Click to expand</summary>
|
479 |
+
|
480 |
+
</details>
|
481 |
+
-->
|
482 |
+
|
483 |
+
<!--
|
484 |
+
### Out-of-Scope Use
|
485 |
+
|
486 |
+
*List how the model may foreseeably be misused and address what users ought not to do with the model.*
|
487 |
+
-->
|
488 |
+
|
489 |
+
## Evaluation
|
490 |
+
|
491 |
+
### Metrics
|
492 |
+
|
493 |
+
#### Semantic Similarity
|
494 |
+
|
495 |
+
* Dataset: `val`
|
496 |
+
* Evaluated with [<code>EmbeddingSimilarityEvaluator</code>](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.EmbeddingSimilarityEvaluator)
|
497 |
+
|
498 |
+
| Metric | Value |
|
499 |
+
|:--------------------|:-----------|
|
500 |
+
| pearson_cosine | 0.9481 |
|
501 |
+
| **spearman_cosine** | **0.5635** |
|
502 |
+
|
503 |
+
<!--
|
504 |
+
## Bias, Risks and Limitations
|
505 |
+
|
506 |
+
*What are the known or foreseeable issues stemming from this model? You could also flag here known failure cases or weaknesses of the model.*
|
507 |
+
-->
|
508 |
+
|
509 |
+
<!--
|
510 |
+
### Recommendations
|
511 |
+
|
512 |
+
*What are recommendations with respect to the foreseeable issues? For example, filtering explicit content.*
|
513 |
+
-->
|
514 |
+
|
515 |
+
## Training Details
|
516 |
+
|
517 |
+
### Training Dataset
|
518 |
+
|
519 |
+
#### Unnamed Dataset
|
520 |
+
|
521 |
+
* Size: 901,028 training samples
|
522 |
+
* Columns: <code>sentence_0</code>, <code>sentence_1</code>, and <code>label</code>
|
523 |
+
* Approximate statistics based on the first 1000 samples:
|
524 |
+
| | sentence_0 | sentence_1 | label |
|
525 |
+
|:--------|:--------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------|:---------------------------------------------------------------|
|
526 |
+
| type | string | string | float |
|
527 |
+
| details | <ul><li>min: 52 tokens</li><li>mean: 332.69 tokens</li><li>max: 2048 tokens</li></ul> | <ul><li>min: 54 tokens</li><li>mean: 353.29 tokens</li><li>max: 2048 tokens</li></ul> | <ul><li>min: 0.0</li><li>mean: 0.49</li><li>max: 1.0</li></ul> |
|
528 |
+
* Samples:
|
529 |
+
| sentence_0 | sentence_1 | label |
|
530 |
+
|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:-----------------|
|
531 |
+
| <code> public static Image load(final InputStream input, String format, Point dimension) throws CoreException {<br> MultiStatus status = new MultiStatus(GraphVizActivator.ID, 0, "Errors occurred while running Graphviz", null);<br> File dotInput = null, dotOutput = null;<br> ByteArrayOutputStream dotContents = new ByteArrayOutputStream();<br> try {<br> dotInput = File.createTempFile(TMP_FILE_PREFIX, DOT_EXTENSION);<br> dotOutput = File.createTempFile(TMP_FILE_PREFIX, "." + format);<br> dotOutput.delete();<br> FileOutputStream tmpDotOutputStream = null;<br> try {<br> IOUtils.copy(input, dotContents);<br> tmpDotOutputStream = new FileOutputStream(dotInput);<br> IOUtils.copy(new ByteArrayInputStream(dotContents.toByteArray()), tmpDotOutputStream);<br> } finally {<br> IOUtils.closeQuietly(tmpDotOutputStream);<br> }<br> IStatus result = runDot(format, dimension, dotInp...</code> | <code> public final Matrix3D<E> read(final URL url) throws IOException {<br> if (url == null) {<br> throw new IllegalArgumentException("url must not be null");<br> }<br> InputStream inputStream = null;<br> try {<br> inputStream = url.openStream();<br> return read(inputStream);<br> } catch (IOException e) {<br> throw e;<br> } finally {<br> MatrixIOUtils.closeQuietly(inputStream);<br> }<br> }<br></code> | <code>0.0</code> |
|
532 |
+
| <code> public List<PathObject> fetchPath(BoardObject board) throws NetworkException {<br> if (boardPathMap.containsKey(board.getId())) {<br> return boardPathMap.get(board.getId()).getChildren();<br> }<br> HttpClient client = HttpConfig.newInstance();<br> HttpGet get = new HttpGet(HttpConfig.bbsURL() + HttpConfig.BBS_0AN_BOARD + board.getId());<br> try {<br> HttpResponse response = client.execute(get);<br> HttpEntity entity = response.getEntity();<br> Document doc = XmlOperator.readDocument(entity.getContent());<br> PathObject parent = new PathObject();<br> BBSBodyParseHelper.parsePathList(doc, parent);<br> parent = searchAndCreatePathFromRoot(parent);<br> boardPathMap.put(board.getId(), parent);<br> return parent.getChildren();<br> } catch (Exception e) {<br> e.printStackTrace();<br> throw new NetworkException(e);<br> }<br> }<br></code> | <code> public static void readDefault() {<br> ClassLoader l = Skeleton.class.getClassLoader();<br> URL url;<br> if (l != null) {<br> url = l.getResource(DEFAULT_LOC);<br> } else {<br> url = ClassLoader.getSystemResource(DEFAULT_LOC);<br> }<br> if (url == null) {<br> Out.error(ErrorMessages.SKEL_IO_ERROR_DEFAULT);<br> throw new GeneratorException();<br> }<br> try {<br> InputStreamReader reader = new InputStreamReader(url.openStream());<br> readSkel(new BufferedReader(reader));<br> } catch (IOException e) {<br> Out.error(ErrorMessages.SKEL_IO_ERROR_DEFAULT);<br> throw new GeneratorException();<br> }<br> }<br></code> | <code>0.0</code> |
|
533 |
+
| <code> public boolean copyFile(File source, File dest) {<br> try {<br> FileReader in = new FileReader(source);<br> FileWriter out = new FileWriter(dest);<br> int c;<br> while ((c = in.read()) != -1) out.write(c);<br> in.close();<br> out.close();<br> return true;<br> } catch (Exception e) {<br> return false;<br> }<br> }<br></code> | <code> public static boolean encodeFileToFile(String infile, String outfile) {<br> boolean success = false;<br> java.io.InputStream in = null;<br> java.io.OutputStream out = null;<br> try {<br> in = new Base64.InputStream(new java.io.BufferedInputStream(new java.io.FileInputStream(infile)), Base64.ENCODE);<br> out = new java.io.BufferedOutputStream(new java.io.FileOutputStream(outfile));<br> byte[] buffer = new byte[65536];<br> int read = -1;<br> while ((read = in.read(buffer)) >= 0) {<br> out.write(buffer, 0, read);<br> }<br> success = true;<br> } catch (java.io.IOException exc) {<br> exc.printStackTrace();<br> } finally {<br> try {<br> in.close();<br> } catch (Exception exc) {<br> }<br> try {<br> out.close();<br> } catch (Exception exc) {<br> }<br> }<br> return success;<br> }<br></code> | <code>1.0</code> |
|
534 |
+
* Loss: [<code>CosineSimilarityLoss</code>](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#cosinesimilarityloss) with these parameters:
|
535 |
+
```json
|
536 |
+
{
|
537 |
+
"loss_fct": "torch.nn.modules.loss.MSELoss"
|
538 |
+
}
|
539 |
+
```
|
540 |
+
|
541 |
+
### Training Hyperparameters
|
542 |
+
#### Non-Default Hyperparameters
|
543 |
+
|
544 |
+
- `eval_strategy`: steps
|
545 |
+
- `per_device_train_batch_size`: 32
|
546 |
+
- `per_device_eval_batch_size`: 32
|
547 |
+
- `num_train_epochs`: 1
|
548 |
+
- `fp16`: True
|
549 |
+
- `multi_dataset_batch_sampler`: round_robin
|
550 |
+
|
551 |
+
#### All Hyperparameters
|
552 |
+
<details><summary>Click to expand</summary>
|
553 |
+
|
554 |
+
- `overwrite_output_dir`: False
|
555 |
+
- `do_predict`: False
|
556 |
+
- `eval_strategy`: steps
|
557 |
+
- `prediction_loss_only`: True
|
558 |
+
- `per_device_train_batch_size`: 32
|
559 |
+
- `per_device_eval_batch_size`: 32
|
560 |
+
- `per_gpu_train_batch_size`: None
|
561 |
+
- `per_gpu_eval_batch_size`: None
|
562 |
+
- `gradient_accumulation_steps`: 1
|
563 |
+
- `eval_accumulation_steps`: None
|
564 |
+
- `torch_empty_cache_steps`: None
|
565 |
+
- `learning_rate`: 5e-05
|
566 |
+
- `weight_decay`: 0.0
|
567 |
+
- `adam_beta1`: 0.9
|
568 |
+
- `adam_beta2`: 0.999
|
569 |
+
- `adam_epsilon`: 1e-08
|
570 |
+
- `max_grad_norm`: 1
|
571 |
+
- `num_train_epochs`: 1
|
572 |
+
- `max_steps`: -1
|
573 |
+
- `lr_scheduler_type`: linear
|
574 |
+
- `lr_scheduler_kwargs`: {}
|
575 |
+
- `warmup_ratio`: 0.0
|
576 |
+
- `warmup_steps`: 0
|
577 |
+
- `log_level`: passive
|
578 |
+
- `log_level_replica`: warning
|
579 |
+
- `log_on_each_node`: True
|
580 |
+
- `logging_nan_inf_filter`: True
|
581 |
+
- `save_safetensors`: True
|
582 |
+
- `save_on_each_node`: False
|
583 |
+
- `save_only_model`: False
|
584 |
+
- `restore_callback_states_from_checkpoint`: False
|
585 |
+
- `no_cuda`: False
|
586 |
+
- `use_cpu`: False
|
587 |
+
- `use_mps_device`: False
|
588 |
+
- `seed`: 42
|
589 |
+
- `data_seed`: None
|
590 |
+
- `jit_mode_eval`: False
|
591 |
+
- `use_ipex`: False
|
592 |
+
- `bf16`: False
|
593 |
+
- `fp16`: True
|
594 |
+
- `fp16_opt_level`: O1
|
595 |
+
- `half_precision_backend`: auto
|
596 |
+
- `bf16_full_eval`: False
|
597 |
+
- `fp16_full_eval`: False
|
598 |
+
- `tf32`: None
|
599 |
+
- `local_rank`: 0
|
600 |
+
- `ddp_backend`: None
|
601 |
+
- `tpu_num_cores`: None
|
602 |
+
- `tpu_metrics_debug`: False
|
603 |
+
- `debug`: []
|
604 |
+
- `dataloader_drop_last`: False
|
605 |
+
- `dataloader_num_workers`: 0
|
606 |
+
- `dataloader_prefetch_factor`: None
|
607 |
+
- `past_index`: -1
|
608 |
+
- `disable_tqdm`: False
|
609 |
+
- `remove_unused_columns`: True
|
610 |
+
- `label_names`: None
|
611 |
+
- `load_best_model_at_end`: False
|
612 |
+
- `ignore_data_skip`: False
|
613 |
+
- `fsdp`: []
|
614 |
+
- `fsdp_min_num_params`: 0
|
615 |
+
- `fsdp_config`: {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}
|
616 |
+
- `tp_size`: 0
|
617 |
+
- `fsdp_transformer_layer_cls_to_wrap`: None
|
618 |
+
- `accelerator_config`: {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'non_blocking': False, 'gradient_accumulation_kwargs': None}
|
619 |
+
- `deepspeed`: None
|
620 |
+
- `label_smoothing_factor`: 0.0
|
621 |
+
- `optim`: adamw_torch
|
622 |
+
- `optim_args`: None
|
623 |
+
- `adafactor`: False
|
624 |
+
- `group_by_length`: False
|
625 |
+
- `length_column_name`: length
|
626 |
+
- `ddp_find_unused_parameters`: None
|
627 |
+
- `ddp_bucket_cap_mb`: None
|
628 |
+
- `ddp_broadcast_buffers`: False
|
629 |
+
- `dataloader_pin_memory`: True
|
630 |
+
- `dataloader_persistent_workers`: False
|
631 |
+
- `skip_memory_metrics`: True
|
632 |
+
- `use_legacy_prediction_loop`: False
|
633 |
+
- `push_to_hub`: False
|
634 |
+
- `resume_from_checkpoint`: None
|
635 |
+
- `hub_model_id`: None
|
636 |
+
- `hub_strategy`: every_save
|
637 |
+
- `hub_private_repo`: None
|
638 |
+
- `hub_always_push`: False
|
639 |
+
- `gradient_checkpointing`: False
|
640 |
+
- `gradient_checkpointing_kwargs`: None
|
641 |
+
- `include_inputs_for_metrics`: False
|
642 |
+
- `include_for_metrics`: []
|
643 |
+
- `eval_do_concat_batches`: True
|
644 |
+
- `fp16_backend`: auto
|
645 |
+
- `push_to_hub_model_id`: None
|
646 |
+
- `push_to_hub_organization`: None
|
647 |
+
- `mp_parameters`:
|
648 |
+
- `auto_find_batch_size`: False
|
649 |
+
- `full_determinism`: False
|
650 |
+
- `torchdynamo`: None
|
651 |
+
- `ray_scope`: last
|
652 |
+
- `ddp_timeout`: 1800
|
653 |
+
- `torch_compile`: False
|
654 |
+
- `torch_compile_backend`: None
|
655 |
+
- `torch_compile_mode`: None
|
656 |
+
- `dispatch_batches`: None
|
657 |
+
- `split_batches`: None
|
658 |
+
- `include_tokens_per_second`: False
|
659 |
+
- `include_num_input_tokens_seen`: False
|
660 |
+
- `neftune_noise_alpha`: None
|
661 |
+
- `optim_target_modules`: None
|
662 |
+
- `batch_eval_metrics`: False
|
663 |
+
- `eval_on_start`: False
|
664 |
+
- `use_liger_kernel`: False
|
665 |
+
- `eval_use_gather_object`: False
|
666 |
+
- `average_tokens_across_devices`: False
|
667 |
+
- `prompts`: None
|
668 |
+
- `batch_sampler`: batch_sampler
|
669 |
+
- `multi_dataset_batch_sampler`: round_robin
|
670 |
+
|
671 |
+
</details>
|
672 |
+
|
673 |
+
### Training Logs
|
674 |
+
| Epoch | Step | Training Loss | val_spearman_cosine |
|
675 |
+
|:------:|:-----:|:-------------:|:-------------------:|
|
676 |
+
| 0.0178 | 500 | 0.1622 | - |
|
677 |
+
| 0.0355 | 1000 | 0.0124 | 0.5702 |
|
678 |
+
| 0.0533 | 1500 | 0.0087 | - |
|
679 |
+
| 0.0710 | 2000 | 0.0064 | 0.5686 |
|
680 |
+
| 0.0888 | 2500 | 0.0048 | - |
|
681 |
+
| 0.1065 | 3000 | 0.0046 | 0.5753 |
|
682 |
+
| 0.1243 | 3500 | 0.0036 | - |
|
683 |
+
| 0.1421 | 4000 | 0.0039 | 0.5745 |
|
684 |
+
| 0.1598 | 4500 | 0.0036 | - |
|
685 |
+
| 0.1776 | 5000 | 0.0035 | 0.5637 |
|
686 |
+
| 0.1953 | 5500 | 0.0036 | - |
|
687 |
+
| 0.2131 | 6000 | 0.0027 | 0.5615 |
|
688 |
+
| 0.2308 | 6500 | 0.002 | - |
|
689 |
+
| 0.2486 | 7000 | 0.0019 | 0.5660 |
|
690 |
+
| 0.2664 | 7500 | 0.0017 | - |
|
691 |
+
| 0.2841 | 8000 | 0.0017 | 0.5622 |
|
692 |
+
| 0.3019 | 8500 | 0.0019 | - |
|
693 |
+
| 0.3196 | 9000 | 0.0017 | 0.5583 |
|
694 |
+
| 0.3374 | 9500 | 0.0012 | - |
|
695 |
+
| 0.3551 | 10000 | 0.0013 | 0.5547 |
|
696 |
+
| 0.3729 | 10500 | 0.0015 | - |
|
697 |
+
| 0.3907 | 11000 | 0.0011 | 0.5631 |
|
698 |
+
| 0.4084 | 11500 | 0.0012 | - |
|
699 |
+
| 0.4262 | 12000 | 0.0013 | 0.5630 |
|
700 |
+
| 0.4439 | 12500 | 0.001 | - |
|
701 |
+
| 0.4617 | 13000 | 0.0009 | 0.5607 |
|
702 |
+
| 0.4794 | 13500 | 0.0007 | - |
|
703 |
+
| 0.4972 | 14000 | 0.001 | 0.5590 |
|
704 |
+
| 0.5150 | 14500 | 0.001 | - |
|
705 |
+
| 0.5327 | 15000 | 0.0009 | 0.5572 |
|
706 |
+
| 0.5505 | 15500 | 0.0007 | - |
|
707 |
+
| 0.5682 | 16000 | 0.0006 | 0.5607 |
|
708 |
+
| 0.5860 | 16500 | 0.0007 | - |
|
709 |
+
| 0.6037 | 17000 | 0.0006 | 0.5675 |
|
710 |
+
| 0.6215 | 17500 | 0.0007 | - |
|
711 |
+
| 0.6392 | 18000 | 0.0009 | 0.5610 |
|
712 |
+
| 0.6570 | 18500 | 0.0008 | - |
|
713 |
+
| 0.6748 | 19000 | 0.0007 | 0.5583 |
|
714 |
+
| 0.6925 | 19500 | 0.0006 | - |
|
715 |
+
| 0.7103 | 20000 | 0.0006 | 0.5662 |
|
716 |
+
| 0.7280 | 20500 | 0.0007 | - |
|
717 |
+
| 0.7458 | 21000 | 0.0005 | 0.5659 |
|
718 |
+
| 0.7635 | 21500 | 0.0004 | - |
|
719 |
+
| 0.7813 | 22000 | 0.0006 | 0.5667 |
|
720 |
+
| 0.7991 | 22500 | 0.0006 | - |
|
721 |
+
| 0.8168 | 23000 | 0.0006 | 0.5644 |
|
722 |
+
| 0.8346 | 23500 | 0.0005 | - |
|
723 |
+
| 0.8523 | 24000 | 0.0003 | 0.5629 |
|
724 |
+
| 0.8701 | 24500 | 0.0005 | - |
|
725 |
+
| 0.8878 | 25000 | 0.0005 | 0.5642 |
|
726 |
+
| 0.9056 | 25500 | 0.0006 | - |
|
727 |
+
| 0.9234 | 26000 | 0.0006 | 0.5640 |
|
728 |
+
| 0.9411 | 26500 | 0.0004 | - |
|
729 |
+
| 0.9589 | 27000 | 0.0007 | 0.5634 |
|
730 |
+
| 0.9766 | 27500 | 0.0004 | - |
|
731 |
+
| 0.9944 | 28000 | 0.0005 | 0.5635 |
|
732 |
+
| 1.0 | 28158 | - | 0.5635 |
|
733 |
+
|
734 |
+
|
735 |
+
### Framework Versions
|
736 |
+
- Python: 3.11.11
|
737 |
+
- Sentence Transformers: 4.0.1
|
738 |
+
- Transformers: 4.50.3
|
739 |
+
- PyTorch: 2.6.0+cu124
|
740 |
+
- Accelerate: 1.5.2
|
741 |
+
- Datasets: 3.5.0
|
742 |
+
- Tokenizers: 0.21.1
|
743 |
+
|
744 |
+
## Citation
|
745 |
+
|
746 |
+
### BibTeX
|
747 |
+
|
748 |
+
#### Sentence Transformers
|
749 |
+
```bibtex
|
750 |
+
@inproceedings{reimers-2019-sentence-bert,
|
751 |
+
title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks",
|
752 |
+
author = "Reimers, Nils and Gurevych, Iryna",
|
753 |
+
booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing",
|
754 |
+
month = "11",
|
755 |
+
year = "2019",
|
756 |
+
publisher = "Association for Computational Linguistics",
|
757 |
+
url = "https://arxiv.org/abs/1908.10084",
|
758 |
+
}
|
759 |
+
```
|
760 |
+
|
761 |
+
<!--
|
762 |
+
## Glossary
|
763 |
+
|
764 |
+
*Clearly define terms in order to be accessible across audiences.*
|
765 |
+
-->
|
766 |
+
|
767 |
+
<!--
|
768 |
+
## Model Card Authors
|
769 |
+
|
770 |
+
*Lists the people who create the model card, providing recognition and accountability for the detailed work that goes into its construction.*
|
771 |
+
-->
|
772 |
+
|
773 |
+
<!--
|
774 |
+
## Model Card Contact
|
775 |
+
|
776 |
+
*Provides a way for people who have updates to the Model Card, suggestions, or questions, to contact the Model Card authors.*
|
777 |
+
-->
|
added_tokens.json
ADDED
@@ -0,0 +1,6 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"</s>": 50001,
|
3 |
+
"<mask>": 50003,
|
4 |
+
"<s>": 50000,
|
5 |
+
"<unk>": 50002
|
6 |
+
}
|
config.json
ADDED
@@ -0,0 +1,49 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"architectures": [
|
3 |
+
"ModernBertModel"
|
4 |
+
],
|
5 |
+
"attention_bias": false,
|
6 |
+
"attention_dropout": 0.0,
|
7 |
+
"attention_probs_dropout_prob": 0.1,
|
8 |
+
"bos_token_id": 50000,
|
9 |
+
"classifier_activation": "gelu",
|
10 |
+
"classifier_bias": false,
|
11 |
+
"classifier_dropout": 0.0,
|
12 |
+
"classifier_pooling": "cls",
|
13 |
+
"cls_token_id": 50281,
|
14 |
+
"decoder_bias": true,
|
15 |
+
"deterministic_flash_attn": false,
|
16 |
+
"embedding_dropout": 0.0,
|
17 |
+
"eos_token_id": 50001,
|
18 |
+
"global_attn_every_n_layers": 3,
|
19 |
+
"global_rope_theta": 160000.0,
|
20 |
+
"hidden_activation": "gelu",
|
21 |
+
"hidden_dropout_prob": 0.1,
|
22 |
+
"hidden_size": 768,
|
23 |
+
"initializer_cutoff_factor": 2.0,
|
24 |
+
"initializer_range": 0.02,
|
25 |
+
"intermediate_size": 3072,
|
26 |
+
"local_attention": 128,
|
27 |
+
"local_attention_rope_theta": 10000,
|
28 |
+
"local_attention_window": 128,
|
29 |
+
"local_rope_theta": 10000.0,
|
30 |
+
"max_position_embeddings": 2048,
|
31 |
+
"mlp_bias": false,
|
32 |
+
"mlp_dropout": 0.0,
|
33 |
+
"model_type": "modernbert",
|
34 |
+
"norm_bias": false,
|
35 |
+
"norm_eps": 1e-05,
|
36 |
+
"num_attention_heads": 12,
|
37 |
+
"num_hidden_layers": 12,
|
38 |
+
"pad_token_id": 0,
|
39 |
+
"reference_compile": true,
|
40 |
+
"repad_logits_with_grad": false,
|
41 |
+
"rope_theta": 160000,
|
42 |
+
"sep_token_id": 50282,
|
43 |
+
"sparse_pred_ignore_index": -100,
|
44 |
+
"sparse_prediction": false,
|
45 |
+
"torch_dtype": "float32",
|
46 |
+
"transformers_version": "4.50.3",
|
47 |
+
"type_vocab_size": 2,
|
48 |
+
"vocab_size": 50004
|
49 |
+
}
|
config_sentence_transformers.json
ADDED
@@ -0,0 +1,10 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"__version__": {
|
3 |
+
"sentence_transformers": "4.0.1",
|
4 |
+
"transformers": "4.50.3",
|
5 |
+
"pytorch": "2.6.0+cu124"
|
6 |
+
},
|
7 |
+
"prompts": {},
|
8 |
+
"default_prompt_name": null,
|
9 |
+
"similarity_fn_name": "cosine"
|
10 |
+
}
|
merges.txt
ADDED
The diff for this file is too large to render.
See raw diff
|
|
model.safetensors
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:1f1f72bbfe8d3f5de1ac4763808bb610c40aaddcc39905532d47928deb1aecfc
|
3 |
+
size 606681112
|
modules.json
ADDED
@@ -0,0 +1,14 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
[
|
2 |
+
{
|
3 |
+
"idx": 0,
|
4 |
+
"name": "0",
|
5 |
+
"path": "",
|
6 |
+
"type": "sentence_transformers.models.Transformer"
|
7 |
+
},
|
8 |
+
{
|
9 |
+
"idx": 1,
|
10 |
+
"name": "1",
|
11 |
+
"path": "1_Pooling",
|
12 |
+
"type": "sentence_transformers.models.Pooling"
|
13 |
+
}
|
14 |
+
]
|
sentence_bert_config.json
ADDED
@@ -0,0 +1,4 @@
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"max_seq_length": 2048,
|
3 |
+
"do_lower_case": false
|
4 |
+
}
|
special_tokens_map.json
ADDED
@@ -0,0 +1,51 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
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|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"bos_token": {
|
3 |
+
"content": "<s>",
|
4 |
+
"lstrip": false,
|
5 |
+
"normalized": false,
|
6 |
+
"rstrip": false,
|
7 |
+
"single_word": false
|
8 |
+
},
|
9 |
+
"cls_token": {
|
10 |
+
"content": "<s>",
|
11 |
+
"lstrip": false,
|
12 |
+
"normalized": false,
|
13 |
+
"rstrip": false,
|
14 |
+
"single_word": false
|
15 |
+
},
|
16 |
+
"eos_token": {
|
17 |
+
"content": "</s>",
|
18 |
+
"lstrip": false,
|
19 |
+
"normalized": false,
|
20 |
+
"rstrip": false,
|
21 |
+
"single_word": false
|
22 |
+
},
|
23 |
+
"mask_token": {
|
24 |
+
"content": "<mask>",
|
25 |
+
"lstrip": true,
|
26 |
+
"normalized": false,
|
27 |
+
"rstrip": false,
|
28 |
+
"single_word": false
|
29 |
+
},
|
30 |
+
"pad_token": {
|
31 |
+
"content": "[PAD]",
|
32 |
+
"lstrip": false,
|
33 |
+
"normalized": false,
|
34 |
+
"rstrip": false,
|
35 |
+
"single_word": false
|
36 |
+
},
|
37 |
+
"sep_token": {
|
38 |
+
"content": "</s>",
|
39 |
+
"lstrip": false,
|
40 |
+
"normalized": false,
|
41 |
+
"rstrip": false,
|
42 |
+
"single_word": false
|
43 |
+
},
|
44 |
+
"unk_token": {
|
45 |
+
"content": "<unk>",
|
46 |
+
"lstrip": false,
|
47 |
+
"normalized": false,
|
48 |
+
"rstrip": false,
|
49 |
+
"single_word": false
|
50 |
+
}
|
51 |
+
}
|
tokenizer.json
ADDED
The diff for this file is too large to render.
See raw diff
|
|
tokenizer_config.json
ADDED
@@ -0,0 +1,97 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
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|
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|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"add_prefix_space": false,
|
3 |
+
"added_tokens_decoder": {
|
4 |
+
"0": {
|
5 |
+
"content": "[PAD]",
|
6 |
+
"lstrip": false,
|
7 |
+
"normalized": false,
|
8 |
+
"rstrip": false,
|
9 |
+
"single_word": false,
|
10 |
+
"special": true
|
11 |
+
},
|
12 |
+
"1": {
|
13 |
+
"content": "[UNK]",
|
14 |
+
"lstrip": false,
|
15 |
+
"normalized": false,
|
16 |
+
"rstrip": false,
|
17 |
+
"single_word": false,
|
18 |
+
"special": true
|
19 |
+
},
|
20 |
+
"2": {
|
21 |
+
"content": "[CLS]",
|
22 |
+
"lstrip": false,
|
23 |
+
"normalized": false,
|
24 |
+
"rstrip": false,
|
25 |
+
"single_word": false,
|
26 |
+
"special": true
|
27 |
+
},
|
28 |
+
"3": {
|
29 |
+
"content": "[SEP]",
|
30 |
+
"lstrip": false,
|
31 |
+
"normalized": false,
|
32 |
+
"rstrip": false,
|
33 |
+
"single_word": false,
|
34 |
+
"special": true
|
35 |
+
},
|
36 |
+
"4": {
|
37 |
+
"content": "[MASK]",
|
38 |
+
"lstrip": false,
|
39 |
+
"normalized": false,
|
40 |
+
"rstrip": false,
|
41 |
+
"single_word": false,
|
42 |
+
"special": true
|
43 |
+
},
|
44 |
+
"50000": {
|
45 |
+
"content": "<s>",
|
46 |
+
"lstrip": false,
|
47 |
+
"normalized": false,
|
48 |
+
"rstrip": false,
|
49 |
+
"single_word": false,
|
50 |
+
"special": true
|
51 |
+
},
|
52 |
+
"50001": {
|
53 |
+
"content": "</s>",
|
54 |
+
"lstrip": false,
|
55 |
+
"normalized": false,
|
56 |
+
"rstrip": false,
|
57 |
+
"single_word": false,
|
58 |
+
"special": true
|
59 |
+
},
|
60 |
+
"50002": {
|
61 |
+
"content": "<unk>",
|
62 |
+
"lstrip": false,
|
63 |
+
"normalized": false,
|
64 |
+
"rstrip": false,
|
65 |
+
"single_word": false,
|
66 |
+
"special": true
|
67 |
+
},
|
68 |
+
"50003": {
|
69 |
+
"content": "<mask>",
|
70 |
+
"lstrip": true,
|
71 |
+
"normalized": false,
|
72 |
+
"rstrip": false,
|
73 |
+
"single_word": false,
|
74 |
+
"special": true
|
75 |
+
}
|
76 |
+
},
|
77 |
+
"bos_token": "<s>",
|
78 |
+
"clean_up_tokenization_spaces": false,
|
79 |
+
"cls_token": "<s>",
|
80 |
+
"eos_token": "</s>",
|
81 |
+
"errors": "replace",
|
82 |
+
"extra_special_tokens": {},
|
83 |
+
"mask_token": "<mask>",
|
84 |
+
"max_length": null,
|
85 |
+
"model_max_length": 1000000000000000019884624838656,
|
86 |
+
"pad_to_multiple_of": null,
|
87 |
+
"pad_token": "[PAD]",
|
88 |
+
"pad_token_type_id": 0,
|
89 |
+
"padding_side": "right",
|
90 |
+
"sep_token": "</s>",
|
91 |
+
"stride": 0,
|
92 |
+
"tokenizer_class": "RobertaTokenizer",
|
93 |
+
"trim_offsets": true,
|
94 |
+
"truncation_side": "right",
|
95 |
+
"truncation_strategy": "longest_first",
|
96 |
+
"unk_token": "<unk>"
|
97 |
+
}
|
vocab.json
ADDED
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|
|